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检索条件"机构=Computer Graphics and Computer Vision Laboratory"
152 条 记 录,以下是11-20 订阅
排序:
Video Test-Time Adaptation for Action Recognition
Video Test-Time Adaptation for Action Recognition
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Conference on computer vision and Pattern Recognition (CVPR)
作者: Wei Lin Muhammad Jehanzeb Mirza Mateusz Kozinski Horst Possegger Hilde Kuehne Horst Bischof Institute for Computer Graphics and Vision Graz University of Technology Austria Christian Doppler Laboratory for Semantic 3D Computer Vision Christian Doppler Laboratory for Embedded Machine Learning Goethe University Frankfurt Germany MIT-IBM Watson AI Lab
Although action recognition systems can achieve top performance when evaluated on in-distribution test points, they are vulnerable to unanticipated distribution shifts in test data. However, test-time adaptation of vi...
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Enforcing connectivity of 3D linear structures using their 2D projections
arXiv
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arXiv 2022年
作者: Oner, Doruk Osman, Hussein Kozinski, Mateusz Fua, Pascal Computer Vision Laboratory École Polytechnique Fédérale de Lausanne Switzerland Institute of Computer Graphics and Vision Graz University of Technology Austria
Many biological and medical tasks require the delineation of 3D curvilinear structures such as blood vessels and neurites from image volumes. This is typically done using neural networks trained by minimizing voxel-wi... 详细信息
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Sit Back and Relax: Learning to Drive Incrementally in All Weather Conditions
Sit Back and Relax: Learning to Drive Incrementally in All W...
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IEEE Symposium on Intelligent Vehicle
作者: Stefan Leitner M. Jehanzeb Mirza Wei Lin Jakub Micorek Marc Masana Mateusz Kozinski Horst Possegger Horst Bischof Institute for Computer Graphics and Vision Graz University of Technology Austria Christian Doppler Laboratory for Embedded Machine Learning Christian Doppler Laboratory for Semantic 3D Computer Vision Silicon Austria Labs TU Graz - SAL Dependable Embedded Systems Lab
In autonomous driving scenarios, current object detection models show strong performance when tested in clear weather. However, their performance deteriorates significantly when tested in degrading weather conditions....
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vision-Language Guidance for LiDAR-based Unsupervised 3D Object Detection
arXiv
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arXiv 2024年
作者: Fruhwirth-Reisinger, Christian Lin, Wei Malić, Dušan Bischof, Horst Possegger, Horst Christian Doppler Laboratory for Embedded Machine Learning Austria Institute of Computer Graphics and Vision Graz University of Technology Austria Institute for Machine Learning Johannes Kepler University Linz Austria
Accurate 3D object detection in LiDAR point clouds is crucial for autonomous driving systems. To achieve state-of-the-art performance, the supervised training of detectors requires large amounts of human-annotated dat... 详细信息
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Enhanced Data Augmentation Using Synthetic Data for Brain Tumour Segmentation  1
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Challenge on Brain Tumor Segmentation, BraTS 2023, International Challenge on Cross-Modality Domain Adaptation for Medical Image Segmentation, CrossMoDA 2023, held in conjunction with the Medical Image Computing for computer Assisted Intervention Conference, MICCAI 2023
作者: Ferreira, André Solak, Naida Li, Jianning Dammann, Philipp Kleesiek, Jens Alves, Victor Egger, Jan Center Algoritmi/LASI University of Minho Braga4710-057 Portugal Computer Algorithms for Medicine Laboratory Graz Austria University Medicine Essen Girardetstraße 2 Essen45131 Germany University Medicine Essen Hufelandstraße 55 Essen45147 Germany Partner Site Essen Hufelandstraße 55 Essen45147 Germany Institute of Computer Graphics and Vision Graz University of Technology Inffeldgasse 16 Graz8010 Austria Department of Neurosurgery and Spine Surgery University Hospital Essen Essen Germany
Deep Learning is the state-of-the-art technology for segmenting brain tumours. However, this requires a lot of high-quality data, which is difficult to obtain, especially in the medical field. Therefore, our solutions... 详细信息
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DRT: Detection Refinement for Multiple Object Tracking  32
DRT: Detection Refinement for Multiple Object Tracking
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32nd British Machine vision Conference, BMVC 2021
作者: Wang, Bisheng Fruhwirth-Reisinger, Christian Possegger, Horst Bischof, Horst Cao, Guo School of Computer Science and Engineering Nanjing University of Science and Technology China Christian Doppler Laboratory for Embedded Machine Learning Austria Institute of Computer Graphics and Vision Graz University of Technology Austria
Deep learning methods have led to remarkable progress in multiple object tracking (MOT). However, when tracking in crowded scenes, existing methods still suffer from both inaccurate and missing detections. This paper ... 详细信息
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Sit Back and Relax: Learning to Drive Incrementally in All Weather Conditions
arXiv
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arXiv 2023年
作者: Leitner, Stefan Mirza, M. Jehanzeb Lin, Wei Micorek, Jakub Masana, Marc Kozinski, Mateusz Possegger, Horst Bischof, Horst Institute for Computer Graphics and Vision Graz University of Technology Austria Christian Doppler Laboratory for Embedded Machine Learning Austria Christian Doppler Laboratory for Semantic 3D Computer Vision Austria TU Graz SAL Dependable Embedded Systems Lab Silicon Austria Labs Austria
In autonomous driving scenarios, current object detection models show strong performance when tested in clear weather. However, their performance deteriorates significantly when tested in degrading weather conditions.... 详细信息
来源: 评论
EC-SfM: Efficient Covisibility-based Structure-from-Motion for Both Sequential and Unordered Images
arXiv
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arXiv 2023年
作者: Ye, Zhichao Bao, Chong Zhou, Xin Liu, Haomin Bao, Hujun Zhang, Guofeng State Key Laboratory of Computer Aided Design and Computer Graphics Zhejiang University Hangzhou310058 China SenseTime Research Hangzhou311215 China ZJU-SenseTime Joint Lab of 3D Vision China
Structure-from-Motion is a technology used to obtain scene structure through image collection, which is a fundamental problem in computer vision. For unordered Internet images, SfM is very slow due to the lack of prio... 详细信息
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LaFTer: Label-Free Tuning of Zero-shot Classifier using Language and Unlabeled Image Collections
arXiv
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arXiv 2023年
作者: Mirza, M. Jehanzeb Karlinsky, Leonid Lin, Wei Kozinski, Mateusz Possegger, Horst Feris, Rogerio Bischof, Horst Institute of Computer Graphics and Vision TU Graz Austria Christian Doppler Laboratory for Embedded Machine Learning Austria MIT-IBM Watson AI Lab United States
Recently, large-scale pre-trained vision and Language (VL) models have set a new state-of-the-art (SOTA) in zero-shot visual classification enabling open-vocabulary recognition of potentially unlimited set of categori... 详细信息
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Adjusting the Ground Truth Annotations for Connectivity-Based Learning to Delineate
arXiv
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arXiv 2021年
作者: Oner, Doruk Kozinski, Mateusz Citraro, Lenoardo Fua, Pascal The Computer Vision Laboratory EPFL Switzerland The Institute of Computer Vision and Graphics TU Graz Austria
Deep learning-based approaches to delineating 3D structure depend on accurate annotations to train the networks. Yet in practice, people, no matter how conscientious, have trouble precisely delineating in 3D and on a ... 详细信息
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